A radar antenna calibration method includes: forming a detection matrix from signals detected by an arrangement of receive antennas in response to chirps transmitted by an arrangement of transmit antennas, the detection matrix having multiple rows corresponding to the chirps, multiple columns corresponding to a signal sample, and multiple planes corresponding the receive antennas; deriving a range matrix by performing a frequency transform on a portion of each row of the detection matrix; extracting a slice of the range matrix, with different rows of the slice being associated with different chirps and with different receive antennas; deriving a velocity matrix from the extracted slice by performing a frequency transform on a portion of each column of the extracted slice; analyzing the velocity matrix to determine a current peak width; and adjusting, based on the current peak width, phase shifts associated with one or more of the receive antennas.

A radar system is provided that includes a radar transceiver integrated circuit (IC) configurable to transmit a first frame of chirps, and another radar transceiver IC configurable to transmit a second frame of chirps at a time delay ΔT, wherein ΔT=T.sub.c/K, K≥2 and T.sub.c is an elapsed time from a start of one chirp in the first frame and the second frame and a start of a next chirp in the first frame and the second frame, wherein the radar system is configured to determine a velocity of an object in a field of view of the radar system based on first digital intermediate frequency signals generated responsive to receiving reflected chirps of the first frame and second digital IF signals generated responsive to receiving reflected chirps of the time delayed second frame, wherein the maximum measurable velocity is increased by a factor of K.

This document describes techniques and systems for reducing a state based on sensor data from an Inertial Measurement Unit (IMU) and radar. The techniques and systems use inertial sensor data from an IMU as well as radar data to reduce states of a user equipment, such as power, access, and information states. These states represent power used, an amount of access permitted, or an amount of information provided by the user equipment. The techniques manage the user equipment's states to correspond to a user's engagement with the user equipment, which can save power, reduce unwarranted access, and reduce an amount of information provided when the user is not engaged with the user equipment, thereby protecting the user's privacy.

This document describes techniques and systems for authentication management through IMU and radar. The techniques and systems use inertial sensor data from an inertial measurement unit (IMU) and/or radar data to manage authentication for a computing device. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for computing-device authentication.

According to one embodiment, a system includes a radar device, a storage device and a controller. The radar device is configured to transmit a first radio wave to an object in a direction of a first angle of the object. The storage device is configured to store first information capable of specifying that a radio wave is transmitted to the first angle of the object by the radar device. The controller is configured to control a direction of a second radio wave to be transmitted by the radar device after the transmission of the first radio wave to a second angle of the object different from the first angle.

In an embodiment, a method for tracking targets includes: receiving data from a radar sensor of a radar; processing the received data to detect targets; identifying a first geometric feature of a first detected target at a first time step, the first detected target being associated to a first track; identifying a second geometric feature of a second detected target at a second time step; determining an error value based on the first and second geometric features; and associating the second detected target to the first track based on the error value.

A method of radar signal processing includes providing an analog front end (AFE) including an amplifier coupled between an antenna and an ADC in a receive path, where an ADC output is coupled to an input of an elastic ADC buffer (elastic buffer) including a divided memory with for writing samples from the ADC (samples) while reading earlier written samples to a first signal processor by a high speed interface. A transmit path includes at least one power amplifier provided by the AFE coupled to drive an antenna. A Greatest Common Divisor (GCD) is determined across all chirps in a radar frame programmed to be used. For each frame a sample size for the elastic buffer is dynamically controlled constant to be equal to the GCD for reading samples from one memory block and writing samples to another memory block throughout all chirps in the frame.

In an embodiment, a method for tracking targets includes: receiving data from a radar sensor of a radar; processing the received data to detect targets; identifying a first geometric feature of a first detected target at a first time step, the first detected target being associated to a first track; identifying a second geometric feature of a second detected target at a second time step; determining an error value based on the first and second geometric features; and associating the second detected target to the first track based on the error value.

Systems and methods to use radar systems for radio frequency identification (RFID) applications. The radar systems can be adapted to use RFID communications protocols and methods to enhance the usefulness of radar systems beyond the determination of the presence, distance, direction and/or speed of a vehicle or object, to additionally include the transmission of data such as object identification and additional messages or data.

A system for measuring medical data characterizing a subject to be monitored, the system including radar sensor/s and/or electro-optical sensor/s. The medical data, which may include pulse and/or respiratory rate and/or temperature of the subject to be monitored, are measured remotely, thereby providing standoff detection and reducing risk of infection to medical personnel.